In India, that no easy task given that the country has hundreds of millions of poor people, but with many variations and different needs among them, and a fiscal deficit that constrains the government’s capacity for generosity.

The revised poverty line that India proposed in 2011 met with so much criticism that Indian officials said that year that the provision of benefits would not be linked to that poverty line, but could include people above it. Even so, there has to be some method for choosing these beneficiaries.

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Poverty expert Abhijit Banerjee, an economist at the Massachusetts Institute of Technology, said that rather than government programs choosing the poor people it intends to help, doing the reverse is a lot more efficient, research shows.

Asking those who need benefits to step forward and identify themselves is, counter-intuitively, the most accurate and viable way of identifying the poor for the purposes of poverty-alleviation, Mr. Banerjee said in a lecture at a university in the western city of Pune on Saturday.

Mr. Banerjee, who is also a co-founder of the Poverty Action Lab, a research initiative at MIT that uses techniques from clinical drug testing to test the efficacy of anti-poverty efforts, laid out three possible ways governments can identifiy the poor people they need to help.

The methods were tested in field research in Indonesiain 2008 and 2009, in which households were selected for a cash transfer using these methods. Partial results from the experiment were published in a Poverty Lab newsletter earlier this month.

As part of the experiment, over 640 village households were also individually surveyed by researchers for an independent assessment of how many poor familes there were. The accuracy of the methods of finding poverty program recipients was gauged by comparing the number of households living on $2 or less a day and the number of households that got the cash transfer using each method.

In an ideal world, the most comprehensive way to identify the poor would be to visit each and every household in the country, collect their income data and then set a cut-off, said Mr. Banerjee. That, of course, is a logistical nightmare and impractical.Indiacarries out a population census just once in 10 years, for example.

Instead, it’s easier to check if a household owns a set of easy-to-observe consumer durables. For instance, if a family owns a refrigerator or a motorcycle, it’s not poor. This is much less cumbersome than measuring every household’s income.

The second method is asking members of a community to identify the poor within their community. This can be done either by asking each member of the community or asking only the community leaders.

The research found both of these methods arrived at similar results in terms of selecting recipients for the cash transfer.

But Mr. Banerjee said research found both of these methods were inferior to self-targeting — offering benefits to everyone on the assumption that only those genuinely in need would bother to show up to collect them. One example of this, he says, isIndia’s National Rural Employment Guarantee Act, which promises 100 days of employment in manual unskilled jobs every year to adult members of every rural household at the statutory minimum wage.

“The philosophy of the NREGA is if they take up a job digging ditches in the middle of the summer, they are poor, because no one else would want that job,” says Mr. Banerjee.

To test the third method, Mr. Banerje carried out an additional experiment involving 400 Indonesian villages. The benefits were generous — potential recipients were offered cash equaling 11% of their annual consumption for the last six years.

The participants were told not to bother applying if they were not poor because government workers would visit their homes to vet their applications.

The results of the experiment showed that self-targeting works better than the previous two methods. More poor people and less ineligible applicants signed up than in either of the other two methods.

The other question was whether the results improved if it was made more difficult for people to sign up, for instance by making people travel five miles or wait in a queue for three hours to sign up.

The result was many more poor people failed to show up, particularly those on whom a difficult process extracted more of a toll, such as disabled people or single mothers with children to get back to.

“When you increase the cost, the poorest people also drop out,” said Mr. Banerjee.

Yet even the self-targeting method was surprisingly wide of the mark said Mr. Banerjee. As many as 40% of the people identified as eligible for the benefit by researchers in their baseline survey did not come forward to sign up for help, said Mr. Banerjee.

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